Sort by
Refine Your Search
-
: 30 September 2026 Apply now How can generative AI (GenAI) support Health Technology Assessment (HTA) of medicines? HTA bodies and technology developers are already experimenting with GenAI, but
-
‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations that optimize these indicators; Compute Pareto frontiers under
-
to define glycan features that govern influenza attachment and to develop advanced in vitro receptor models reflecting airway tissues. Your tools: Interdisciplinary receptor analysis: you will work with
-
contribute to the development of state-specific clinical guidelines. You will also write scientific articles and contribute to dissemination activities. Throughout the project, you will work in close
-
(or nearing completion of) an MSc program in Human Geography, International Development Studies, Critical Agrarian Studies, or a related Social Science discipline; An interest in the impacts of land use
-
and Finance. Given the current developments in this field, knowledge/research on digital/data science and AI, and the impact upon Finance – including its role for enabling societal transitions - is
-
funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about developing cutting-edge AI techniques to enhance interaction
-
. Implementation You will develop data analysis scripts to assess and improve data quality. Your main responsibility will be to collaborate with PhD candidates and the postdoctoral researcher on the representation
-
or vanish over centuries? In this position, you will develop, evaluate, and fine-tune cutting-edge AI methods—LLMs, word embeddings, and clustering—to track how word meanings evolve across multilingual
-
a Postdoctoral Researcher in the group of dr Marino , you will play a central role in advancing the group's research through the development and application of state-of-the-art immunopeptidomics